The photon production and collective flows from magnetic induced fusion and splitting in early stage of high energy nuclear collision

We present an event-by-event study of photon production in the early stage of high energy nuclear collisions, where the system is dominant by highly occupied of gluons. The photons are produced through the gluon fusion and splitting processes when strong magnetic field is included. We study the spectra and collective flows of the photons and show their dependence on transverse momentum $q_{T}$. It is found that the photons from the boost invariant evolving glasma provide visible enhancement on spectrum and obvious contribution on $v_{2}$ of total the direct photons in large $q_{T}$ region. The results, by weighting on top of parton-hadron-string dynamics (PHSD) model, agree even better with experiment measurements in Au-Au 20\%-40\% centrality collisions at $\sqrt{s_{NN}}=200$GeV.Comment: 8 pages, 6 figure

Numerical simulation of hydrodynamics and reaeration over a stepped spillway by the SPH method

Aerated flows are characterized by complex hydrodynamics and mass-transfer processes. As a Lagrangian method, smoothed particle hydrodynamics (SPH) has a significant advantage in tracking the air-water interface in turbulent flows. This paper presents the application of an SPH method to investigate hydrodynamics and reaeration over stepped spillways. In the SPH method, the entrainment of dissolved oxygen (DO) is studied using a multiphase mass transfer SPH method for reaeration. The numerical results are compared with the hydrodynamics data from Chanson and DO data from Cheng. The simulation results show that velocity distribution and the location of free-surface aeration inception agree with the experimental results. Compared with the experimental results, the distribution of DO concentration over the stepped spillway is consistent with the measurement results. The study shows that the two-phase DO mass transfer SPH model is reliable and reasonable for simulating the hydrodynamics characteristics and reaeration process

Finite-temperature violation of the anomalous transverse Wiedemann-Franz law

The Wiedemann-Franz (WF) law links the ratio of electronic charge and heat conductivity to fundamental constants. It has been tested in numerous solids, but the extent of its relevance to the anomalous transverse transport, which represents the topological nature of the wave function, remains an open question. Here we present a study of anomalous transverse response in the noncollinear antiferromagnet Mn$_{3}$Ge extended from room temperature down to sub-Kelvin temperature and find that the anomalous Lorenz ratio remains close to the Sommerfeld value up to 100 K, but not above. The finite-temperature violation of the WF correlation is caused by a mismatch between the thermal and electrical summations of the Berry curvature, rather than the inelastic scattering as observed in ordinary metals. This interpretation is backed by our theoretical calculations, which reveals a competition between the temperature and the Berry curvature distribution. The accuracy of the experiment is supported by the verification of the Bridgman relation between the anomalous Ettingshausen and Nernst effects. Our results identify the anomalous Lorenz ratio as an extremely sensitive probe of Berry spectrum near the chemical potential.Comment: 9 pages,6 figures, Supplemental Material include

Zhang, et al, Expression of iKIR-HLA-Cw in patients with inflammatory bowel disease Expression of iKIR-HLA-Cw in patients with inflammatory bowel disease

Abstract Objective. To investigate the distribution of inhibitory killer cell immunoglobulin-like receptor (iKIR) and its ligand human leukocyte antigen C locus (HLA-Cw) in patients with inflammatory bowel disease (IBD), and explore whether iKIR/HLA-Cw combinations are associated with IBD susceptibility. Methods. The iKIR in 100 patients with ulcerative colitis (UC), 52 patients with Crohn's disease (CD) and 106 randomly ethnically matched healthy controls was phenotyped by sequence-specific primer PCR (PCR-SSP). HLA-Cw was phenotyped by CLOCUS SSP UNITRAY ® . The combination of HLA-Cw and its corresponding iKIR in individual was analyzed subsequently. Results. The KIR2DL1 and KIR2DL3 gene phenotype frequencies in UC patients were 0.710 and 0.620 respectively, both significantly lower than those in healthy controls, and the KIR2DL1 gene phenotype frequency in CD patients was 0.731, significantly lower than that in healthy controls. KIR2DL1-HLA-C2 combination in patients with UC and CD were 0.380 and 0.404 respectively, both significantly lower than that in healthy controls. Conclusion. The susceptibility to IBD is associated with decreased KIR2DL1-HLA-C2 combination

Comparative analysis and integrative classification of NCI60 cell lines and primary tumors using gene expression profiling data

BACKGROUND: NCI60 cell lines are derived from cancers of 9 tissue origins and have been invaluable in vitro models for cancer research and anti-cancer drug screen. Although extensive studies have been carried out to assess the molecular features of NCI60 cell lines related to cancer and their sensitivities to more than 100,000 chemical compounds, it remains unclear if and how well these cell lines represent or model their tumor tissues of origin. Identification and confirmation of correct origins of NCI60 cell lines are critical to their usage as model systems and to translate in vitro studies into clinical potentials. Here we report a direct comparison between NCI60 cell lines and primary tumors by analyzing global gene expression profiles. RESULTS: Comparative analysis suggested that 51 of 59 cell lines we analyzed represent their presumed tumors of origin. Taking advantage of available clinical information of primary tumor samples used to generate gene expression profiling data, we further classified those cell lines with the correct origins into different subtypes of cancer or different stages in cancer development. For example, 6 of 7 non-small cell lung cancer cell lines were classified as lung adenocarcinomas and all of them were classified into late stages in tumor progression. CONCLUSION: Taken together, we developed and applied a novel approach for systematic comparative analysis and integrative classification of NCI60 cell lines and primary tumors. Our results could provide guidance to the selection of appropriate cell lines for cancer research and pharmaceutical compound screenings. Moreover, this gene expression profile based approach can be generally applied to evaluate experimental model systems such as cell lines and animal models for human diseases

AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration

Diffusion models are emerging expressive generative models, in which a large number of time steps (inference steps) are required for a single image generation. To accelerate such tedious process, reducing steps uniformly is considered as an undisputed principle of diffusion models. We consider that such a uniform assumption is not the optimal solution in practice; i.e., we can find different optimal time steps for different models. Therefore, we propose to search the optimal time steps sequence and compressed model architecture in a unified framework to achieve effective image generation for diffusion models without any further training. Specifically, we first design a unified search space that consists of all possible time steps and various architectures. Then, a two stage evolutionary algorithm is introduced to find the optimal solution in the designed search space. To further accelerate the search process, we employ FID score between generated and real samples to estimate the performance of the sampled examples. As a result, the proposed method is (i).training-free, obtaining the optimal time steps and model architecture without any training process; (ii). orthogonal to most advanced diffusion samplers and can be integrated to gain better sample quality. (iii). generalized, where the searched time steps and architectures can be directly applied on different diffusion models with the same guidance scale. Experimental results show that our method achieves excellent performance by using only a few time steps, e.g. 17.86 FID score on ImageNet 64 $\times$ 64 with only four steps, compared to 138.66 with DDIM. The code is available at https://github.com/lilijiangg/AutoDiffusion